Package index
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A1Benchmark - Yahoo Webscope S5 – A1 Benchmark (Real)
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A2Benchmark - Yahoo Webscope S5 – A2 Benchmark (Synthetic)
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A3Benchmark - Yahoo Webscope S5 – A3 Benchmark (Synthetic with Outliers)
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A4Benchmark - Yahoo Webscope S5 – A4 Benchmark (Synthetic with Anomalies and CPs)
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detect() - Detect events in time series
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examples_anomalies - Time series for anomaly detection
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examples_changepoints - Time series for change point detection
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examples_harbinger - Time series for event detection
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examples_motifs - Time series for motif/discord discovery
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gecco - GECCO Challenge 2018 – Water Quality Time Series
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han_autoencoder() - Anomaly detector using autoencoders
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hanc_ml() - Anomaly detector based on ML classification
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hanct_dtw() - Anomaly detector using DTW
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hanct_kmeans() - Anomaly detector using kmeans
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hanr_arima() - Anomaly detector using ARIMA
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hanr_emd() - Anomaly detector using EMD
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hanr_fbiad() - Anomaly detector using FBIAD
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hanr_fft() - Anomaly detector using FFT
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hanr_fft_amoc() - Anomaly Detector using FFT with AMOC Cutoff
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hanr_fft_amoc_cusum() - Anomaly Detector using FFT with AMOC and CUSUM Cutoff
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hanr_fft_binseg() - Anomaly Detector using FFT with Binary Segmentation Cutoff
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hanr_fft_binseg_cusum() - Anomaly Detector using FFT with BinSeg and CUSUM Cutoff
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hanr_fft_sma() - Anomaly Detector using Adaptive FFT and Moving Average
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hanr_garch() - Anomaly detector using GARCH
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hanr_histogram() - Anomaly detector using histograms
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hanr_ml() - Anomaly detector based on ML regression
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hanr_remd() - Anomaly detector using REMD
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hanr_rtad() - Anomaly and change point detector using RTAD
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hanr_wavelet() - Anomaly detector using Wavelets
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har_ensemble() - Harbinger Ensemble
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har_eval() - Evaluation of event detection
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har_eval_soft() - Evaluation of event detection (SoftED)
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har_plot() - Plot event detection on a time series
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harbinger() - Harbinger
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harutils() - Harbinger Utilities
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hcp_amoc() - At Most One Change (AMOC)
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hcp_binseg() - Binary Segmentation (BinSeg)
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hcp_cf_arima() - Change Finder using ARIMA
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hcp_cf_ets() - Change Finder using ETS
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hcp_cf_lr() - Change Finder using Linear Regression
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hcp_chow() - Chow Test (structural break)
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hcp_garch() - Change Finder using GARCH
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hcp_gft() - Generalized Fluctuation Test (GFT)
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hcp_pelt() - Pruned Exact Linear Time (PELT)
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hcp_scp() - Seminal change point
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hdis_mp() - Discord discovery using Matrix Profile
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hdis_sax() - Discord discovery using SAX
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hmo_mp() - Motif discovery using Matrix Profile
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hmo_sax() - Motif discovery using SAX
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hmo_xsax() - Motif discovery using XSAX
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hmu_pca() - Multivariate anomaly detector using PCA
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loadfulldata() - Load full dataset from mini data object
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mas() - Moving average smoothing
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mit_bih_MLII - MIT-BIH Arrhythmia Database – MLII Lead
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mit_bih_V1 - MIT-BIH Arrhythmia Database – V1 Lead
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mit_bih_V2 - MIT-BIH Arrhythmia Database – V2 Lead
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mit_bih_V5 - MIT-BIH Arrhythmia Database – V5 Lead
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nab_artificialWithAnomaly - Numenta Anomaly Benchmark (NAB) – artificialWithAnomaly
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nab_realAWSCloudwatch - Numenta Anomaly Benchmark (NAB) realAWSCloudwatch
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nab_realAdExchange - Numenta Anomaly Benchmark (NAB) – realAdExchange
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nab_realKnownCause - Numenta Anomaly Benchmark (NAB) realKnownCause
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nab_realTraffic - Numenta Anomaly Benchmark (NAB) realTraffic
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nab_realTweets - Numenta Anomaly Benchmark (NAB) realTweets
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oil_3w_Type_1 - Oil Wells Dataset – Type 1
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oil_3w_Type_2 - Oil Wells Dataset – Type 2
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oil_3w_Type_4 - Oil Wells Dataset – Type 4
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oil_3w_Type_5 - Oil Wells Dataset – Type 5
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oil_3w_Type_6 - Oil Wells Dataset – Type 6
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oil_3w_Type_7 - Oil Wells Dataset – Type 7
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oil_3w_Type_8 - Oil Wells Dataset – Type 8
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trans_sax() - SAX transformation
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trans_xsax() - XSAX transformation
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ucr_ecg - UCR Anomaly Archive – ECG
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ucr_int_bleeding - UCR Anomaly Archive – Internal Bleeding
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ucr_nasa - UCR Anomaly Archive – NASA Spacecraft
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ucr_power_demand - UCR Anomaly Archive – Italian Power Demand